Siemens' AI Agent for Industrial Automation: Automating Engineering Processes

Siemens has announced new capabilities for its Eigen Engineering Agent, an AI-powered system developed for industrial automation engineering. In addition to tasks such as PLC programming, HMI visualization, and device configuration, the system is designed to automate processes between electrical engineering and software development.
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What is Eigen Engineering Agent?

Eigen Engineering Agent is an AI-based engineering tool developed by Siemens specifically for industrial automation engineering. Unlike general-purpose artificial intelligence systems, this system is tailored for automation engineering workflows; it can plan, execute, and validate assigned tasks.

The system operates seamlessly integrated with Siemens' TIA Portal engineering platform. This integration allows engineering tasks to be executed while accounting for program structures, hardware devices, parameters, and other project data utilized in automation projects.

AI Can Program PLCs

One of the standout application areas of Eigen Engineering Agent is PLC programming. By analyzing automation engineering tasks, the system can generate the necessary PLC code and verify the resulting output against project requirements.

According to Siemens, beyond PLC programming, the system can also handle tasks such as HMI visualization and device configuration.

This approach primarily aims to automate repetitive engineering procedures, enabling engineers to dedicate their time to more complex tasks such as system architecture, control strategy, and commissioning.

Integration Between ECAD and TIA Portal

Among Siemens' new capabilities is ECAD integration.

In traditional engineering workflows, transferring data generated during electrical design into project data within automation software often requires a substantial amount of manual work. Eigen Engineering Agent aims to bridge this gap by analyzing information within electrical design files and transferring it directly into TIA Portal projects.

The system can parse electrical design data in formats such as XML and AML, detect inconsistencies, instantiate devices within the TIA Portal project, and assist in generating PLC tags based on wiring and connection details.

This feature is designed to reduce repetitive tasks involved in the information flow between electrical engineering and automation software.

Generating Automation Projects from Natural Language

Another noteworthy feature of Eigen Engineering Agent is its ability to convert machine descriptions written in natural language into functional automation projects.

Engineers can describe a machine’s stations, incorporated hardware, and operational logic using natural language. Based on this input, the system can build a project structure compliant with the Siemens Automation Framework.

The generated project can subsequently be opened within TIA Portal and further refined by the engineer. This approach aims to reduce repetitive tasks during the initial configuration phase of an automation project.

AI Validating Its Own Results

In industrial automation systems, simply generating code is insufficient. The generated control logic must strictly comply with project requirements, system architecture, and relevant engineering standards.

For this reason, Eigen Engineering Agent is not designed merely as a code generation tool. According to Siemens, the system can break complex engineering tasks down into smaller steps, execute those steps, and validate the results.

Unlike general-purpose AI tools, this approach seeks to establish a more comprehensive engineering process that accounts for the technical context of the automation project.

Tested in Over 100 Companies

Siemens announced that prior to its commercial release, Eigen Engineering Agent underwent pilot testing across more than 100 companies in 19 countries.

The pilot trials encompassed diverse engineering tasks, including PLC programming, HMI visualization, device configuration, and documentation.

Based on pilot results published by Siemens, the system executed certain engineering tasks 2 to 5 times faster compared to manual workflows. The company also reported efficiency gains of up to 50% in specific processes and up to an 80% improvement in solution quality.

It should be noted that these figures represent pilot results disclosed by Siemens and do not imply that identical performance will be achieved in every automation project.

Will AI Replace Automation Engineers?

Eigen Engineering Agent serves as a prominent example of the roles AI can assume in industrial automation engineering.

Automating repetitive operations—such as PLC code generation, device configuration, HMI visualization, and documentation—can help engineers reallocate their time toward higher-level system decisions.

However, this does not mean AI will fully replace automation engineers. Designing control architectures, evaluating physical machine behavior, defining safety requirements, commissioning systems, and validating operations under real-world conditions remain processes that require human supervision and deep engineering expertise.

Therefore, rather than viewing Eigen Engineering Agent as a replacement for engineers, it is more accurate to treat it as an AI-based tool that automates a specific subset of tasks within the automation workflow.

The Future of Industrial Automation

The direct integration of artificial intelligence into engineering software and industrial automation workflows represents an important transformation in manufacturing technology.

In the case of Eigen Engineering Agent, AI is not limited to mere text or code generation. It aims to unify information across disparate engineering phases—from electrical design and PLC programming to device configuration and HMI development.

The system developed by Siemens demonstrates that AI in industrial automation is evolving from an advisory assistant into a more autonomous system capable of executing discrete engineering tasks.

In the coming years, how this approach is applied to other automation platforms and increasingly complex production systems will be a key topic at the intersection of AI and industrial engineering.

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